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      <h1 id="Redis-01-Nosql简介"><a href="#Redis-01-Nosql简介" class="headerlink" title="Redis-01-Nosql简介"></a>Redis-01-Nosql简介</h1><h2 id="1-NoSQL概述"><a href="#1-NoSQL概述" class="headerlink" title="1. NoSQL概述"></a>1. NoSQL概述</h2><h3 id="1-1-为什么要使用Nosql"><a href="#1-1-为什么要使用Nosql" class="headerlink" title="1.1 为什么要使用Nosql?"></a>1.1 为什么要使用Nosql?</h3><p><strong>2020年：大数据时代！</strong></p>
<ul>
<li><strong>单机MySQL的年代</strong></li>
</ul>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200404155818.png" alt=""></p>
<p>90年代，一个基本网站访问量一般不会太大，单个数据库完全足够！</p>
<p>那个时候，更多的是去使用Html~(服务器完全没有太大的压力)</p>
<p>思考一下：这种情况下，整个网站的瓶颈是什么？</p>
<ol>
<li>数据量如果太大，一个机器都放不下了！</li>
<li>数据的索引 <strong>（Mysql超过300万，要建对应索引：B+树）</strong></li>
<li>访问量（读写混合），一个服务器承受不了！</li>
</ol>
<p><strong>只要出现上面三个情况之一，那么就必须要晋级</strong></p>
<ul>
<li><strong>Memcached(缓存) + Mysql + 垂直拆分（读写分离）</strong></li>
</ul>
<p>网站百分之80的情况下都在读，所以说希望减轻数据库的压力，使用<strong>缓存来保证效率。</strong></p>
<p>发展过程：</p>
<ol>
<li>优化数据结构和索引</li>
<li>文件缓存（IO）</li>
<li>Memcached(缓存) === <strong>当时最热门的技术</strong></li>
</ol>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200404160532.png" alt=""></p>
<a id="more"></a>

<ul>
<li><strong>分库分表 + 水平拆分（MySQL集群）</strong></li>
</ul>
<p>技术和业务在发展的同时，对人的要求也越来越高。</p>
<p>本质：数据读（读+写）</p>
<p>早些年：MyISAM:表锁（查数据锁整个表）</p>
<p>早些年：Innodb:行锁（查数据只锁这一行）</p>
<p><strong>慢慢的就开始分库分表来解决写的压力</strong></p>
<p>Mysql在那个年代推出了表分区，并没有多少公司使用</p>
<p>MySQL集群，很好的的满足了那个年代的需求！</p>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200404162855.png" alt=""></p>
<ul>
<li><strong>如今年代</strong></li>
</ul>
<ol>
<li><p>MySQL等关系型数据库就不够用了!</p>
<p>数据量很多，变化很快~！</p>
<p><strong>json也可以作为数据库使用 （BSON）</strong></p>
</li>
<li><p>MySQL有的时候使用它存储一些比较大的文件，博客，图片！如果有一种专门的数据库来处理这种数据</p>
</li>
<li><p>MySQL压力就会变得十分小（研究如何处理这种问题）大数据的IO压力小，表几乎没法变大</p>
</li>
</ol>
<ul>
<li><strong>目前一个基本的互联网项目！</strong></li>
</ul>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200404164507.png" alt=""></p>
<ul>
<li><strong>为什么要用NoSQL!</strong></li>
</ul>
<p>用户的个人信息，社交网络，地址位置，用户自己产生的数据，用户的日志等等爆发式增加！</p>
<p>这个时候就需要使用NoSQL数据库，可以很好的处理以上的情况！</p>
<h3 id="1-2-什么是NoSQL"><a href="#1-2-什么是NoSQL" class="headerlink" title="1.2 什么是NoSQL?"></a>1.2 什么是NoSQL?</h3><p><strong>关系性数据库：表格（行和列）（POI :java操作excel）</strong></p>
<p>NoSQL == Not only sql</p>
<p>泛指：非关系型数据库</p>
<p>随着web2.0时代的诞生。传统型数据库很难对付web2.0时代，尤其是超大规模的高并发的社区！</p>
<p><strong>Redis：是发展最快的NoSQL技术！</strong></p>
<h3 id="1-3-NoSQL的特点"><a href="#1-3-NoSQL的特点" class="headerlink" title="1.3 NoSQL的特点"></a>1.3 NoSQL的特点</h3><ol>
<li>方便扩展 （数据之间无关系）</li>
<li>大数据量高性能（Redis:一秒可以写8万次，读取11万次）</li>
<li>NoSQL的缓存是一种细粒度的缓存</li>
<li>数据类型是多样的（不需要事先设计数据库！随取随用，如果是数据量非常大的表，关系型数据库就很难设计了）</li>
<li>传统的RDBMS和NoSQL</li>
</ol>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br></pre></td><td class="code"><pre><span class="line">传统的RDBMS:</span><br><span class="line">- 结构化组织</span><br><span class="line">- SQL</span><br><span class="line">- 数据和关系都存在单独的表中 row col</span><br><span class="line">- 数据定义语言</span><br><span class="line">- 严格的一致性</span><br><span class="line">- 基础的事务</span><br><span class="line">- ....</span><br></pre></td></tr></table></figure>

<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><span class="line">NoSQL:</span><br><span class="line">- 不仅仅是数据</span><br><span class="line">- 没有固定的查询语言</span><br><span class="line">- 键值对存储，列存储，文档存储，图形数据库</span><br><span class="line">- CAP定理 和 BASE （异地多活）</span><br><span class="line">- 最终一致性</span><br><span class="line">- 高性能，高可用，高可扩</span><br></pre></td></tr></table></figure>

<h3 id="1-4-了解-3V-3-高"><a href="#1-4-了解-3V-3-高" class="headerlink" title="1.4 了解 3V + 3 高"></a>1.4 了解 3V + 3 高</h3><p>大数据库的3V：主要是描述问题的</p>
<ol>
<li>海量Volume</li>
<li>多样Variety</li>
<li>实时Velocity</li>
</ol>
<p>大数据库的3V高：主要是解决问题的</p>
<ol>
<li>高并发</li>
<li>高可扩（随时水平拆分）</li>
<li>高性能 （保证用户体验和性能）</li>
</ol>
<p><strong>真正在公司中：Nosql + RDBMS 结合使用才是最好的</strong></p>
<h3 id="1-5-阿里巴巴架构演进"><a href="#1-5-阿里巴巴架构演进" class="headerlink" title="1.5 阿里巴巴架构演进"></a>1.5 阿里巴巴架构演进</h3><p><strong>官方文档：【2017年】</strong></p>
<p><a href="https://yq.aliyun.com/articles/161190" target="_blank" rel="noopener">https://yq.aliyun.com/articles/161190</a></p>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200407204725.png" alt=""></p>
<ul>
<li><p>敏捷开发</p>
</li>
<li><p>极限编程</p>
</li>
</ul>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200407205441.png" alt=""></p>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># 1. 商品的基本信息</span></span><br><span class="line">	名称，价格，商品信息</span><br><span class="line">	关系型数据库就可以解决 Mysql/Oracle ()</span><br><span class="line">	推荐文章：阿里云的这群疯子（https://www.huxiu.com/article/267100.html）</span><br><span class="line">	淘宝内部的Mysql 不是大家使用的mysql</span><br><span class="line"><span class="comment"># 2. 商品的描述/评论（文字比较多）</span></span><br><span class="line">	文档型数据库中：Redis/mongoDB</span><br><span class="line"><span class="comment"># 3. 图片</span></span><br><span class="line">	分布式文件系统： FastDFS</span><br><span class="line">	- 淘宝自己的 ：  TFS</span><br><span class="line">	- Google :      GFS</span><br><span class="line">	- Hadoop :      HDFS</span><br><span class="line">	- 阿里云 ：      OSS	</span><br><span class="line"><span class="comment"># 4. 商品的关键字（搜索）</span></span><br><span class="line">	- 搜索引擎： solr  elasticsearch</span><br><span class="line">	- 淘宝：    ISearch (多隆)</span><br><span class="line"><span class="comment"># 5. 商品热门的波段信息</span></span><br><span class="line">	- 内存数据库</span><br><span class="line">	- memcached,Tair,Redis</span><br><span class="line"><span class="comment"># 6. 商品的交易，外部的支付接口</span></span><br><span class="line">	- 三方应用</span><br></pre></td></tr></table></figure>

<p>大型互联网公司的应用问题：</p>
<ol>
<li>数据类型太多了</li>
<li>数据源繁多，经常重构</li>
<li>数据要改造，大面积改造比较麻烦</li>
</ol>
<p>解决问题方案：UDSL(统一数据服务平台)</p>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200407211132.png" alt=""></p>
<p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200407211316.png" alt=""></p>
<h2 id="2-NoSQL的四大分类"><a href="#2-NoSQL的四大分类" class="headerlink" title="2. NoSQL的四大分类"></a>2. NoSQL的四大分类</h2><p><img src="https://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200407212106.png" alt=""></p>
<h3 id="2-1-KV键值对"><a href="#2-1-KV键值对" class="headerlink" title="2.1 KV键值对"></a>2.1 KV键值对</h3><ul>
<li>新浪：<strong>Redis</strong></li>
<li>美团：Redis + Tair</li>
<li>阿里/百度 ： Redis + memecache</li>
</ul>
<h3 id="2-2-文档型数据库（bson）"><a href="#2-2-文档型数据库（bson）" class="headerlink" title="2.2 文档型数据库（bson）"></a>2.2 文档型数据库（bson）</h3><ul>
<li>代表：<strong>MongoDB</strong>(一般必须要掌握)<ul>
<li>MongoDB是一个基于分布式文件存储的数据库（C++编写)，用来处理大量的文档</li>
<li>MongoDB是一个介于关系型数据库和非关系数据库的中间产品！（MongoDB是非关系型数据库中功能最丰富，最像关系型数据库的）</li>
</ul>
</li>
<li>ConthDB</li>
</ul>
<h3 id="2-3-列存储数据库"><a href="#2-3-列存储数据库" class="headerlink" title="2.3 列存储数据库"></a>2.3 列存储数据库</h3><ul>
<li>代表：<strong>HBase</strong></li>
<li>分布式文件系统</li>
</ul>
<h3 id="2-4-图形关系数据库"><a href="#2-4-图形关系数据库" class="headerlink" title="2.4 图形关系数据库"></a>2.4 图形关系数据库</h3><ul>
<li>图形关系数据库（不是存图片，是存图的关系–社交关系之类的）</li>
<li>代表：<strong>Neo4j</strong>,InfoGrid</li>
</ul>

      
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